library(magrittr)
library(tidyverse)
library(Seurat)
library(readxl)
library(cowplot)
library(colorblindr)
library(viridis)
library(magick, lib.loc = "/home/uhlitzf/miniconda3/lib/R/library")
library(ggpubr)
## load global vars:
source("_src/global_vars.R")
# meta_tbl
# clrs
# markers_v6
# markers_v6_super
# cell_type_super_lookup
names(clrs$cell_type) <- str_replace_all(names(clrs$cell_type), "\\.", " ")
names(clrs$cell_type) <- str_replace_all(names(clrs$cell_type), "Ovarian", "Ov")
## load data --------------------------------------
## load cohort embeddings
seu_tbl <- read_tsv("/work/shah/uhlitzf/data/SPECTRUM/freeze/v6/outs_pre/cells.tsv") %>%
mutate(cell_type = ifelse(cell_type == "Monocyte", "Myeloid.cell", cell_type)) %>%
mutate(cell_type = ifelse(cell_type == "Ovarian.cancer.cell", "Ov.cancer.cell", cell_type))
## load consensus data
consOV_tbl <- read_tsv("/work/shah/uhlitzf/data/SPECTRUM/freeze/v6/consensusOV/SPECTRUM_freeze_v6_consensusOV.tsv") %>%
mutate(consensusOV = ordered(consensusOV, levels = names(clrs$consensusOV))) %>%
select(cell_id, consensusOV)
## join data
seu_tbl_full <- seu_tbl %>%
left_join(meta_tbl, by = "sample") %>%
filter(therapy == "pre-Rx", cell_type != "Other", tumor_supersite != "Unknown") %>%
rename(UMAP_1 = umap50_1, UMAP_2 = umap50_2) %>%
mutate(cell_type_super = cell_type_super_lookup[cell_type]) %>%
mutate(cell_type = ordered(str_replace_all(cell_type, "\\.", " "),
levels = names(clrs$cell_type))) %>%
mutate(sort_short_x = ifelse(sort_short == "U" & cell_type_super == "Immune",
"CD45+", ifelse(sort_short == "U" & cell_type_super == "Stromal",
"CD45-", sort_short))) %>%
left_join(consOV_tbl, by = "cell_id")
# seu_tbl_full <- seu_tbl_full %>%
# sample_n(10000)
scRNA compositions
source("_src/comp_plot.R")
# rank_by()
comp_tbl_sample <- seu_tbl_full %>%
filter(therapy == "pre-Rx", cell_type != "Other") %>%
group_by(tumor_subsite, tumor_supersite, tumor_megasite, patient_id_short,
therapy, sort_short_x, consensus_signature, cell_type) %>%
tally() %>%
group_by(tumor_subsite, tumor_supersite, tumor_megasite, patient_id_short,
therapy, sort_short_x, consensus_signature) %>%
mutate(nrel = n/sum(n)*100) %>%
mutate(label_supersite = "Site",
label_therapy = "Rx",
label_mutsig = "Signature") %>%
mutate(tumor_supersite = ordered(tumor_supersite, levels = rev(names(clrs$tumor_supersite)))) %>%
mutate(sample_id = paste(tumor_subsite, patient_id_short, therapy, sort_short_x)) %>%
group_by(sample_id) %>%
mutate(ntotal = sum(n)) %>%
filter(ntotal > 0) %>%
ungroup()
comp_tbl_consOV <- seu_tbl_full %>%
filter(therapy == "pre-Rx", cell_type != "Other") %>%
group_by(tumor_subsite, tumor_supersite, tumor_megasite, patient_id_short,
therapy, sort_short_x, consensus_signature, consensusOV) %>%
tally %>%
group_by(tumor_subsite, tumor_supersite, tumor_megasite, patient_id_short,
therapy, sort_short_x, consensus_signature) %>%
mutate(nrel = n/sum(n)*100,
log10n = log10(n)) %>%
mutate(tumor_supersite = ordered(tumor_supersite, levels = rev(names(clrs$tumor_supersite)))) %>%
mutate(sample_id = paste(tumor_subsite, patient_id_short, therapy, sort_short_x)) %>%
ungroup
#
# g9 <- default_comp_grid(filter(comp_tbl_consOV, sort_short_x == "CD45-"),
# consensusOV, "Immunoreactive")
# g10 <- default_comp_grid(filter(comp_tbl_consOV, sort_short_x == "CD45-"),
# consensusOV, "Mesenchymal")
# g11 <- default_comp_grid(filter(comp_tbl_consOV, sort_short_x == "CD45-"),
# consensusOV, "Differentiated")
# g12 <- default_comp_grid(filter(comp_tbl_consOV, sort_short_x == "CD45-"),
# consensusOV, "Proliferative")
#
# g13 <- default_comp_grid(filter(comp_tbl_consOV, sort_short_x == "CD45+"),
# consensusOV, "Immunoreactive")
# g14 <- default_comp_grid(filter(comp_tbl_consOV, sort_short_x == "CD45+"),
# consensusOV, "Mesenchymal")
# g15 <- default_comp_grid(filter(comp_tbl_consOV, sort_short_x == "CD45+"),
# consensusOV, "Differentiated")
# g16 <- default_comp_grid(filter(comp_tbl_consOV, sort_short_x == "CD45+"),
# consensusOV, "Proliferative")
# pdf("_fig/002_cohort/002_comp_full.pdf", width = 3.5, height = 12)
# g1;g2;g3;g4;g5;g6;g7;g8;g9;g10;g11;g12;g13;g14;g15;g16
# dev.off()
cell type
Site
cell_types_immune <- str_replace_all(names(cell_type_super_lookup[cell_type_super_lookup=="Immune"]), "\\.", " ")
cell_types_stromal <- str_replace_all(names(cell_type_super_lookup[cell_type_super_lookup=="Stromal"]), "\\.", " ") %>%
str_replace_all("Ovarian", "Ov")
for(i in 1:length(cell_types_immune)){
cat('#### ', cell_types_immune[i],' \n')
plist <- default_comp_grid_list(
filter(comp_tbl_sample, sort_short_x == "CD45+"),
cell_type, cell_types_immune[i], cell_type, mutsig_box = F)
p <- plot_grid(plotlist = plist, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
print(p)
cat(' \n \n')
}
B cell

Plasma cell

T cell

Myeloid cell

Dendritic cell

for(i in 1:length(cell_types_stromal)){
cat('#### ', cell_types_stromal[i],' \n')
plist <- default_comp_grid_list(
filter(comp_tbl_sample, sort_short_x == "CD45-"),
cell_type, cell_types_stromal[i], cell_type, mutsig_box = F)
p <- plot_grid(plotlist = plist, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
print(p)
cat(' \n \n')
}
Endothelial cell

Fibroblast

Ov cancer cell

Signature
cell_types_immune <- str_replace_all(names(cell_type_super_lookup[cell_type_super_lookup=="Immune"]), "\\.", " ")
cell_types_stromal <- str_replace_all(names(cell_type_super_lookup[cell_type_super_lookup=="Stromal"]), "\\.", " ") %>%
str_replace_all("Ovarian", "Ov")
for(i in 1:length(cell_types_immune)){
cat('#### ', cell_types_immune[i],' \n')
plist <- default_comp_grid_list(
filter(comp_tbl_sample, sort_short_x == "CD45+"),
cell_type, cell_types_immune[i], cell_type, site_box = F)
p <- plot_grid(plotlist = plist, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
print(p)
cat(' \n \n')
}
B cell

Plasma cell

T cell

Myeloid cell

Dendritic cell

for(i in 1:length(cell_types_stromal)){
cat('#### ', cell_types_stromal[i],' \n')
plist <- default_comp_grid_list(
filter(comp_tbl_sample, sort_short_x == "CD45-"),
cell_type, cell_types_stromal[i], cell_type, site_box = F)
p <- plot_grid(plotlist = plist, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
print(p)
cat(' \n \n')
}
Endothelial cell

Fibroblast

Ov cancer cell

TCGA
Site
tcga_subtypes <- as.character(unique(consOV_tbl$consensusOV))
for(i in 1:length(tcga_subtypes)){
cat('#### ', tcga_subtypes[i],' \n')
plist <- default_comp_grid_list(
filter(comp_tbl_consOV, sort_short_x == "CD45+"),
consensusOV, tcga_subtypes[i], consensusOV, mutsig_box = F)
p <- plot_grid(plotlist = plist, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
print(p)
cat(' \n \n')
}
Differentiated

Immunoreactive

Mesenchymal

Proliferative

for(i in 1:length(tcga_subtypes)){
cat('#### ', tcga_subtypes[i],' \n')
plist <- default_comp_grid_list(
filter(comp_tbl_consOV, sort_short_x == "CD45-"),
consensusOV, tcga_subtypes[i], consensusOV, mutsig_box = F)
p <- plot_grid(plotlist = plist, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
print(p)
cat(' \n \n')
}
Differentiated

Immunoreactive

Mesenchymal

Proliferative

Signature
tcga_subtypes <- as.character(unique(consOV_tbl$consensusOV))
for(i in 1:length(tcga_subtypes)){
cat('#### ', tcga_subtypes[i],' \n')
plist <- default_comp_grid_list(
filter(comp_tbl_consOV, sort_short_x == "CD45+"),
consensusOV, tcga_subtypes[i], consensusOV, site_box = F)
p <- plot_grid(plotlist = plist, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
print(p)
cat(' \n \n')
}
Differentiated

Immunoreactive

Mesenchymal

Proliferative

for(i in 1:length(tcga_subtypes)){
cat('#### ', tcga_subtypes[i],' \n')
plist <- default_comp_grid_list(
filter(comp_tbl_consOV, sort_short_x == "CD45-"),
consensusOV, tcga_subtypes[i], consensusOV, site_box = F)
p <- plot_grid(plotlist = plist, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
print(p)
cat(' \n \n')
}
Differentiated

Immunoreactive

Mesenchymal

Proliferative

mpIF composition
## meta data for mpIF
source("_src/global_vars.R")
names(clrs$cell_type) <- str_replace_all(names(clrs$cell_type), "\\.", " ")
names(clrs$cell_type) <- str_replace_all(names(clrs$cell_type), "Ovarian", "Ov")
# mpif_pixel <- read_tsv("/work/shah/vazquezi/data/transfers/spectrum/results/mpif/v8/integrate/outputs/cohort_merge/patient/SPECTRUM/all/detection.tsv") %>%
# select(cell_id, compartment = Parent)
#
# mpif_cell_type <- read_tsv("/work/shah/vazquezi/data/transfers/spectrum/results/mpif/v8/integrate/outputs/cohort_merge/patient/SPECTRUM/all/cell_type_manual.tsv") %>%
# left_join(mpif_pixel, by = "cell_id") %>%
# mutate(cell_id = str_remove_all(cell_id, "CD68.TOX.PD1.PDL1.CD8.panCK_CK8-18.DAPI_|_component_data - resolution #1")) %>%
# separate(cell_id, into = c("patient_id", "tumor_subsite", "fov_id", "cell_idx"),
# sep = "_", remove = F) %>%
# mutate(fov_id = paste0(patient_id, "_", tumor_subsite, "_", fov_id),
# slide_id = paste0(patient_id, "_", tumor_subsite))
#
# ## expand for double and triple positive cells (cell type markers)
# mpif_ncell <- mpif_cell_type %>%
# # sample_n(10000) %>%
# mutate(CD68_state_log = CD68_state == "CD68+",
# CD8_state_log = CD8_state == "CD8+",
# panCK_state_log = panCK_state == "panCK+") %>%
# group_by(cell_id) %>%
# mutate(n_cells = sum(CD68_state_log, CD8_state_log, panCK_state_log)) %>%
# select(cell_id, n_cells) %>%
# deframe
#
# mpif_cell_type_expanded <- bind_rows(
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 0]),
# TOX_state == "TOX+" | PD1_state == "PD1+" | PDL1_state == "PDL1+") %>%
# mutate(cell_id = paste0(cell_id, "_0"),
# cell_type = c("Other")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 0]),
# TOX_state == "TOX-" & PD1_state == "PD1-" & PDL1_state == "PDL1-") %>%
# mutate(cell_id = paste0(cell_id, "_0"),
# cell_type = c("Unknown")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 1]),
# CD8_state == "CD8+") %>%
# mutate(cell_id = paste0(cell_id, "_1"),
# cell_type = c("CD8+")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 1]),
# CD68_state == "CD68+") %>%
# mutate(cell_id = paste0(cell_id, "_2"),
# cell_type = c("CD68+")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 1]),
# panCK_state == "panCK+") %>%
# mutate(cell_id = paste0(cell_id, "_3"),
# cell_type = c("panCK+")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 2]),
# CD8_state == "CD8+") %>%
# mutate(cell_id = paste0(cell_id, "_1"),
# cell_type = c("CD8+")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 2]),
# CD68_state == "CD68+") %>%
# mutate(cell_id = paste0(cell_id, "_2"),
# cell_type = c("CD68+")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 2]),
# panCK_state == "panCK+") %>%
# mutate(cell_id = paste0(cell_id, "_3"),
# cell_type = c("panCK+")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 3]),
# CD8_state == "CD8+") %>%
# mutate(cell_id = paste0(cell_id, "_1"),
# cell_type = c("CD8+")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 3]),
# CD68_state == "CD68+") %>%
# mutate(cell_id = paste0(cell_id, "_2"),
# cell_type = c("CD68+")),
# filter(mpif_cell_type, cell_id %in% names(mpif_ncell[mpif_ncell == 3]),
# panCK_state == "panCK+") %>%
# mutate(cell_id = paste0(cell_id, "_3"),
# cell_type = c("panCK+"))
# )
#
# mpif_cell_state_expanded <- mpif_cell_type_expanded %>%
# mutate(cell_state = case_when(
# cell_type == "CD8+" ~ paste0(CD8_state, TOX_state, PD1_state),
# cell_type == "CD68+" ~ paste0(CD68_state, PDL1_state),
# cell_type == "panCK+" ~ paste0(panCK_state, PDL1_state),
# cell_type == "Unknown" ~ "Unknown",
# cell_type == "Other" ~ "Other"
# ))
#
# write_tsv(mpif_cell_state_expanded, "/work/shah/uhlitzf/data/SPECTRUM/mpIF/cell_type_manual_expanded.tsv")
mpif_cell_state_expanded <- read_tsv("/work/shah/uhlitzf/data/SPECTRUM/mpIF/cell_type_manual_expanded.tsv") %>%
select(cell_id, slide_id, fov_id, compartment, cell_type, cell_state, contains("state")) %>%
left_join(select(mpif_meta_tbl, slide_id, patient_id_short, tumor_supersite, tumor_subsite, therapy, sample_id, consensus_signature, tumor_megasite), by = "slide_id") %>%
na.omit() %>%
mutate(sort_short_x = compartment)
## cell state composition fov lvl
mpif_cell_state_n <- mpif_cell_state_expanded %>%
group_by(patient_id_short, tumor_supersite, tumor_subsite, tumor_megasite, therapy, sample_id, fov_id, consensus_signature, cell_state, cell_type) %>%
tally() %>%
group_by(patient_id_short, tumor_supersite, tumor_subsite, tumor_megasite, therapy, sample_id, fov_id, consensus_signature) %>%
mutate(nrel = n/sum(n)) %>%
ungroup()
## cell state composition slide lvl
mpif_cell_state_n_slide <- mpif_cell_state_expanded %>%
group_by(patient_id_short, tumor_supersite, tumor_subsite, tumor_megasite, therapy, sample_id, consensus_signature, cell_state, cell_type) %>%
tally() %>%
group_by(patient_id_short, tumor_supersite, tumor_subsite, tumor_megasite, therapy, sample_id, consensus_signature) %>%
mutate(nrel = n/sum(n)) %>%
ungroup()
## cell state composition slide lvl compartment
mpif_cell_state_n_slide_compartment <- mpif_cell_state_expanded %>%
group_by(patient_id_short, tumor_supersite, tumor_subsite, tumor_megasite, therapy, sample_id, consensus_signature, sort_short_x, cell_state, cell_type) %>%
tally() %>%
group_by(patient_id_short, tumor_supersite, tumor_subsite, tumor_megasite, therapy, sample_id, consensus_signature, sort_short_x) %>%
mutate(nrel = n/sum(n)*100) %>%
ungroup()
cell type
Site
cell_types_mpif <- c("CD8+", "CD68+", "panCK+", "Other", "Unknown")
for(i in 1:length(cell_types_mpif)){
cat('#### ', cell_types_mpif[i],' \n')
plist_t <- default_comp_grid_list(
filter(mpif_cell_state_n_slide_compartment, sort_short_x == "Tumor"),
cell_type, cell_types_mpif[i], cell_state, mutsig_box = F)
plist_s <- default_comp_grid_list(
filter(mpif_cell_state_n_slide_compartment, sort_short_x == "Stroma"),
cell_type, cell_types_mpif[i], cell_state, mutsig_box = F)
pt <- plot_grid(plotlist = plist_t, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
ps <- plot_grid(plotlist = plist_s, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
p <- plot_grid(pt, ps, ncol = 2)
print(p)
cat(' \n \n')
}
CD8+

CD68+

panCK+

Other

Unknown

Signature
cell_types_mpif <- c("CD8+", "CD68+", "panCK+", "Other", "Unknown")
for(i in 1:length(cell_types_mpif)){
cat('#### ', cell_types_mpif[i],' \n')
plist_t <- default_comp_grid_list(
filter(mpif_cell_state_n_slide_compartment, sort_short_x == "Tumor"),
cell_type, cell_types_mpif[i], cell_state, site_box = F)
plist_s <- default_comp_grid_list(
filter(mpif_cell_state_n_slide_compartment, sort_short_x == "Stroma"),
cell_type, cell_types_mpif[i], cell_state, site_box = F)
pt <- plot_grid(plotlist = plist_t, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
ps <- plot_grid(plotlist = plist_s, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
p <- plot_grid(pt, ps, ncol = 2)
print(p)
cat(' \n \n')
}
CD8+

CD68+

panCK+

Other

Unknown

cell state
Site
cell_states_mpif <- names(clrs$cell_state)
for(i in 1:length(cell_states_mpif)){
cat('#### ', cell_states_mpif[i],' \n')
plist_t <- default_comp_grid_list(
filter(mpif_cell_state_n_slide_compartment, sort_short_x == "Tumor"),
cell_state, cell_states_mpif[i], cell_state, mutsig_box = F)
plist_s <- default_comp_grid_list(
filter(mpif_cell_state_n_slide_compartment, sort_short_x == "Stroma"),
cell_state, cell_states_mpif[i], cell_state, mutsig_box = F)
pt <- plot_grid(plotlist = plist_t, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
ps <- plot_grid(plotlist = plist_s, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
p <- plot_grid(pt, ps, ncol = 2)
print(p)
cat(' \n \n')
}
CD8+TOX-PD1-

CD8+TOX-PD1+

CD8+TOX+PD1-

CD8+TOX+PD1+

CD68+PDL1-

CD68+PDL1+

panCK+PDL1-

panCK+PDL1+

Other

Unknown

Signature
cell_states_mpif <- names(clrs$cell_state)
for(i in 1:length(cell_states_mpif)){
cat('#### ', cell_states_mpif[i],' \n')
plist_t <- default_comp_grid_list(
filter(mpif_cell_state_n_slide_compartment, sort_short_x == "Tumor"),
cell_state, cell_states_mpif[i], cell_state, site_box = F)
plist_s <- default_comp_grid_list(
filter(mpif_cell_state_n_slide_compartment, sort_short_x == "Stroma"),
cell_state, cell_states_mpif[i], cell_state, site_box = F)
pt <- plot_grid(plotlist = plist_t, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
ps <- plot_grid(plotlist = plist_s, ncol = 1, align = "v",
rel_heights = c(0.13, 0.13, 0.13, 0.61))
p <- plot_grid(pt, ps, ncol = 2)
print(p)
cat(' \n \n')
}
CD8+TOX-PD1-

CD8+TOX-PD1+

CD8+TOX+PD1-

CD8+TOX+PD1+

CD68+PDL1-

CD68+PDL1+

panCK+PDL1-

panCK+PDL1+

Other

Unknown

correlation
# # seu_cohort <- read_rds("/work/shah/isabl_data_lake/analyses/16/52/1652/cohort_merged.rdata")
# #
# # scrna_markers <- as_tibble(cbind(cell_id = colnames(seu_cohort), FetchData(seu_cohort, c("cell_type", "sample", "CD68", "PDCD1", "CD274", "TOX", "CD8A", "CD8B", "KRT8", "KRT19")))) %>%
# # mutate(CD68_state = ifelse(CD68 > 0, "CD68+", "CD68-"),
# # CD8_state = ifelse(CD8A > 0 | CD8B > 0, "CD8+", "CD8-"),
# # panCK_state = ifelse(KRT8 > 0 | KRT19 > 0, "panCK+", "panCK-"),
# # TOX_state = ifelse(TOX > 0, "TOX+", "TOX-"),
# # PD1_state = ifelse(PDCD1 > 0, "PD1+", "PD1-"),
# # PDL1_state = ifelse(CD274 > 0, "PDL1+", "PDL1-"))
# #
# # write_tsv(scrna_markers, "/work/shah/uhlitzf/data/SPECTRUM/freeze/v5/scrna_mpif_marker_expression.tsv")
#
# scrna_markers <- read_tsv("/work/shah/uhlitzf/data/SPECTRUM/freeze/v5/scrna_mpif_marker_expression.tsv") %>%
# filter(!(CD68_state == "CD68+" & CD8_state == "CD8+"),
# !(CD68_state == "CD68+" & panCK_state == "panCK+"),
# !(CD8_state == "CD8+" & panCK_state == "panCK+")) %>%
# mutate(cell_type_sc = ifelse(CD68_state == "CD68+", "CD68+", ifelse(CD8_state == "CD8+", "CD8+", ifelse(panCK_state == "panCK+", "panCK+", "Other"))),
# cell_state = case_when(
# cell_type_sc == "CD8+" ~ paste0(CD8_state, TOX_state, PD1_state),
# cell_type_sc == "CD68+" ~ paste0(CD68_state, PDL1_state),
# cell_type_sc == "panCK+" ~ paste0(panCK_state, PDL1_state),
# cell_type_sc == "Unknown" ~ "Unknown",
# cell_type_sc == "Other" ~ "Other"
# ))
#
# markers_pos_frac_scrna_celltype <- seu_tbl_full %>%
# # select(cell_id, sample) %>%
# select(cell_id, sample, tumor_supersite, consensus_signature, patient_id_short, sort_short_x) %>%
# left_join(select(scrna_markers, cell_id, cell_type_sc, cell_state), by = "cell_id") %>%
# na.omit() %>%
# group_by(sample, cell_type_sc, tumor_supersite, consensus_signature, patient_id_short, sort_short_x) %>%
# tally %>%
# group_by(sample, tumor_supersite, consensus_signature, patient_id_short, sort_short_x) %>%
# mutate(nrel = n/sum(n)) %>%
# select(sample, cell_type_sc, n, nrel, everything()) %>%
# ungroup
#
# markers_pos_frac_scrna_cellstate <- seu_tbl_full %>%
# # select(cell_id, sample) %>%
# select(cell_id, sample, tumor_supersite, consensus_signature, patient_id_short, sort_short_x) %>%
# left_join(select(scrna_markers, cell_id, cell_type_sc, cell_state), by = "cell_id") %>%
# na.omit() %>%
# group_by(sample, cell_state, cell_type_sc, tumor_supersite, consensus_signature, patient_id_short, sort_short_x) %>%
# tally %>%
# group_by(sample, cell_type_sc, tumor_supersite, consensus_signature, patient_id_short, sort_short_x) %>%
# mutate(nrel = n/sum(n)) %>%
# select(sample, cell_type_sc, cell_state, n, nrel, everything()) %>%
# ungroup
#
# markers_pos_frac_scrna_gene <- seu_tbl_full %>%
# # select(cell_id, sample) %>%
# select(cell_id, sample, cell_type, tumor_supersite, consensus_signature, patient_id_short, sort_short_x) %>%
# left_join(select(scrna_markers, -sample, -cell_type), by = "cell_id") %>%
# na.omit() %>%
# select(-contains("state")) %>%
# mutate(cell_type = str_replace_all(cell_type, "\\.", " ")) %>%
# gather(gene, value, -cell_id, -sample, -cell_type, -tumor_supersite,
# -consensus_signature, -patient_id_short, -sort_short_x, -cell_type_sc) %>%
# mutate(gene_state = value > 0) %>%
# group_by(gene, sample, tumor_supersite, consensus_signature, patient_id_short, sort_short_x) %>%
# mutate(n = sum(gene_state),
# nrel = n/length(n)) %>%
# ungroup %>%
# distinct(gene, sample, tumor_supersite, consensus_signature, patient_id_short, sort_short_x, n, nrel) %>%
# select(sample, gene, n, nrel, everything())
mpIF x scRNA correlation
CD45+ cell type correlation
# markers_pos_scrna_mpif <- mpif_cell_state_n_slide_compartment %>%
# select(sample = sample_cd45p, cell_type_sc = cell_type,
# compartment, n_mpif = n, nrel_mpif = nrel) %>%
# group_by(sample, cell_type_sc, compartment) %>%
# summarise(n_mpif = sum(n_mpif), nrel_mpif = sum(nrel_mpif)) %>%
# ungroup() %>%
# left_join(markers_pos_frac_scrna_celltype, by = c("sample", "cell_type_sc")) %>%
# filter(sort_short_x == "CD45+",
# cell_type_sc %in% c("CD8+", "CD68+"),
# compartment %in% c("Stroma", "Tumor"))
#
# common_layers <- list(
# facet_wrap(cell_type_sc~compartment, scales = "free"),
# stat_smooth(aes(nrel, nrel_mpif), method = "lm", color = "black"),
# stat_cor(aes(nrel, nrel_mpif), method = "spearman", color = "black"),
# labs(x = "Fraction in scRNA",
# y = "Fraction in mpIF")
# )
#
# p1 <- ggplot(markers_pos_scrna_mpif) +
# geom_point(aes(nrel, nrel_mpif, color = tumor_supersite)) +
# scale_color_manual(values = clrs$tumor_supersite) +
# common_layers
#
# p2 <- ggplot(markers_pos_scrna_mpif) +
# geom_point(aes(nrel, nrel_mpif, color = consensus_signature)) +
# scale_color_manual(values = clrs$consensus_signature) +
# common_layers
#
# plot_grid(p1, p2)
CD45+ cell state correlation
# markers_pos_scrna_mpif_state <- mpif_cell_state_n_slide_compartment %>%
# group_by(sample_cd45p, compartment, cell_type) %>%
# mutate(nrel_state = n/sum(n)) %>%
# select(sample = sample_cd45p, cell_type_sc = cell_type,
# compartment, n_mpif = n, nrel_mpif = nrel_state, cell_state) %>%
# left_join(markers_pos_frac_scrna_cellstate, by = c("sample", "cell_type_sc", "cell_state")) %>%
# filter(sort_short_x == "CD45+",
# cell_state %in% c("CD8+TOX-PD1-", "CD8+TOX+PD1+", "CD68+PDL1-", "CD68+PDL1+"),
# compartment %in% c("Stroma", "Tumor"))
#
# common_layers <- list(
# facet_wrap(cell_state~compartment, scales = "free", ncol = 4),
# geom_smooth(aes(nrel, nrel_mpif), method = "lm", color = "black"),
# stat_cor(aes(nrel, nrel_mpif), method = "spearman", color = "black"),
# labs(x = "Fraction in scRNA",
# y = "Fraction in mpIF")
# )
#
# p1 <- ggplot(markers_pos_scrna_mpif_state) +
# geom_point(aes(nrel, nrel_mpif, color = tumor_supersite)) +
# scale_color_manual(values = clrs$tumor_supersite) +
# common_layers
#
# p2 <- ggplot(markers_pos_scrna_mpif_state) +
# geom_point(aes(nrel, nrel_mpif, color = consensus_signature)) +
# scale_color_manual(values = clrs$consensus_signature) +
# common_layers
#
# plot_grid(p1, p2, ncol = 1)
CD45- cell type correlation
# markers_pos_scrna_mpif_cd45n <- mpif_cell_state_n_slide_compartment %>%
# select(sample = sample_cd45p, cell_type_sc = cell_type,
# compartment, n_mpif = n, nrel_mpif = nrel) %>%
# mutate(sample = str_replace_all(sample, "CD45P", "CD45N")) %>%
# group_by(sample, cell_type_sc, compartment) %>%
# summarise(n_mpif = sum(n_mpif), nrel_mpif = sum(nrel_mpif)) %>%
# ungroup() %>%
# left_join(markers_pos_frac_scrna_celltype, by = c("sample", "cell_type_sc")) %>%
# filter(sort_short_x == "CD45-",
# cell_type_sc %in% c("panCK+"),
# compartment %in% c("Stroma", "Tumor"))
#
# common_layers <- list(
# facet_wrap(cell_type_sc~compartment, scales = "free"),
# stat_smooth(aes(nrel, nrel_mpif), method = "lm", color = "black"),
# stat_cor(aes(nrel, nrel_mpif), method = "pearson", color = "black"),
# labs(x = "Fraction in scRNA",
# y = "Fraction in mpIF")
# )
#
# p1 <- ggplot(markers_pos_scrna_mpif_cd45n) +
# geom_point(aes(nrel, nrel_mpif, color = tumor_supersite)) +
# scale_color_manual(values = clrs$tumor_supersite) +
# common_layers
#
# p2 <- ggplot(markers_pos_scrna_mpif_cd45n) +
# geom_point(aes(nrel, nrel_mpif, color = consensus_signature)) +
# scale_color_manual(values = clrs$consensus_signature) +
# common_layers
#
# plot_grid(p1, p2)
CD45- cell state correlation
# markers_pos_scrna_mpif_state_cd45n <- mpif_cell_state_n_slide_compartment %>%
# group_by(sample_cd45p, compartment, cell_type) %>%
# mutate(nrel_state = n/sum(n)) %>%
# select(sample = sample_cd45p, cell_type_sc = cell_type,
# compartment, n_mpif = n, nrel_mpif = nrel_state, cell_state) %>%
# mutate(sample = str_replace_all(sample, "CD45P", "CD45N")) %>%
# left_join(markers_pos_frac_scrna_cellstate, by = c("sample", "cell_type_sc", "cell_state")) %>%
# filter(sort_short_x == "CD45-",
# cell_state %in% c("panCK+PDL1-", "panCK+PDL1+"),
# compartment %in% c("Stroma", "Tumor"))
#
# common_layers <- list(
# facet_wrap(cell_state~compartment, scales = "free", ncol = 4),
# geom_smooth(aes(nrel, nrel_mpif), method = "lm", color = "black"),
# stat_cor(aes(nrel, nrel_mpif), method = "pearson", color = "black"),
# labs(x = "Fraction in scRNA",
# y = "Fraction in mpIF")
# )
#
# p1 <- ggplot(markers_pos_scrna_mpif_state_cd45n) +
# geom_point(aes(nrel, nrel_mpif, color = tumor_supersite)) +
# scale_color_manual(values = clrs$tumor_supersite) +
# common_layers
#
# p2 <- ggplot(markers_pos_scrna_mpif_state_cd45n) +
# geom_point(aes(nrel, nrel_mpif, color = consensus_signature)) +
# scale_color_manual(values = clrs$consensus_signature) +
# common_layers
#
# plot_grid(p1, p2, ncol = 1)